Association between age, gender, and oral traumatic ulcerative lesions: a retrospective study.

BACKGROUND: Oral traumatic ulcerative lesions (OTUL) are commonly encountered in clinical practice, yet there is limited research on their clinical characteristics and traumatic etiological factors. This retrospective study aimed to analyze the age, gender, clinical characteristics, and traumatic etiological factors in a large cohort of patients with OTUL and provide valuable insights for dental clinicians to optimize patient care and prevention strategies. METHODS: A total of 1543 patients with OTUL were enrolled in this study. Age, gender, medical history, clinical characteristics and traumatic etiological factors were collected and analyzed. Logistic regression analysis was performed to determine the significance of age and gender as factors related to OTUL. RESULTS: The study revealed significant variations in clinical characteristics and traumatic etiological factors among different age groups and between genders. Logistic regression analysis demonstrated that both age and gender were significant factors related to OTUL. CONCLUSION: The clinical characteristics of OTUL and traumatic etiological factors appear to be significantly different according to age and gender. More targeted prevention strategies should be implemented for all age and gender groups.

Vitamin B12 deficiency may play an etiological role in atrophic glossitis and its grading: A clinical case-control study.

BACKGROUND: Existing studies have reported the significant association between atrophic glossitis (AG) and hematinic deficiencies, including iron, folate and vitamin B12 deficiency. However, these findings were inconsistent. AG can be graded as partial or complete atrophy. It is still unclear whether hematinic deficiencies are associated with the grading of AG. METHODS: 236 AG patients and 208 sex- and age-matched healthy controls were enrolled in this study. Hematological tests including complete blood count, and serum levels of folate, ferritin and vitamin B12 were performed. The AG group was divided into those with partial AG and those with complete AG according to the extent of papillary atrophy. Statistical analysis was performed to assess whether hematinic deficiencies are risk factors for AG and its grading. RESULTS: Compared with the healthy controls, AG patients had significantly higher frequencies of vitamin B12 deficiency (68.22%), ferritin deficiency (13.98%) and anemia (21.61%). The differences in hematinic deficiencies and anemia between AG patients and healthy controls changed according to gender and age. The frequencies of serum vitamin B12 deficiency and anemia in the complete AG subgroup were significantly higher than those in the partial AG subgroup. Logistic regression analysis revealed that vitamin B12 deficiency and anemia were significantly correlated with AG and its grading. The AG patients with vitamin B12 deficiency responded well to supplement therapy. CONCLUSION: AG could be an important clinical indicator for potential vitamin B12 deficiency, especially when the degree of tongue atrophy more than 50% and complete atrophy. Vitamin B12 deficiency might play an etiological role in the development of AG.

Effects of nicotine on the metabolism and gene expression profile of Sprague­Dawley rat primary osteoblasts.

Smoking is a risk factor associated with bone and oral diseases, particularly periodontitis. Nicotine, the major toxic component of tobacco, is able to affect the quality and quantity of bone. Osteoblasts serve an important role in bone formation. Thus far, the effects of nicotine on metabolism­associated gene and protein expression in osteoblasts have been controversial and the mechanisms remain unclear. The present study assessed alterations in osteogenic activity by performing a Cell Counting kit­8 assay to investigate proliferation, Annexin V­fluorescein isothiocyanate/propidium iodide staining to investigate apoptosis, alizarin red staining to investigate the formation of mineralized nodules, reverse transcription­quantitative polymerase chain reaction and western blotting to investigate the mRNA and protein levels of collagen I, alkaline phosphatase, bone osteocalcin, bone sialoprotein and osteopontin; and mRNA microarray expression analysis, Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analysis to investigate the whole genome expression profile of Sprague­Dawley (SD) rat primary osteoblasts following treatment with different concentrations of nicotine. The results demonstrated that nicotine inhibited proliferation, promoted early apoptosis and inhibited mineralized nodule formation in a dose­dependent manner by regulating alkaline phosphatase activity and the expression of osteoblast metabolism­associated genes and proteins. According to microarray analysis, several genes associated with bone metabolism and genes in the Hedgehog and Notch signaling pathways were downregulated significantly in nicotine­treated osteoblasts. The results of the present study indicated that nicotine may serve an inhibitory, dose­dependent role in SD rat primary osteoblasts that may be caused by the perturbation of genes and signaling pathways associated with bone formation. These results may provide a theoretical basis for future research regarding bone metabolism and targeted treatment of oral diseases associated with smoking.

Prediction of functional class of proteins and peptides irrespective of sequence homology by support vector machines.

Various computational methods have been used for the prediction of protein and peptide function based on their sequences. A particular challenge is to derive functional properties from sequences that show low or no homology to proteins of known function. Recently, a machine learning method, support vector machines (SVM), have been explored for predicting functional class of proteins and peptides from amino acid sequence derived properties independent of sequence similarity, which have shown promising potential for a wide spectrum of protein and peptide classes including some of the low- and non-homologous proteins. This method can thus be explored as a potential tool to complement alignment-based, clustering-based, and structure-based methods for predicting protein function. This article reviews the strategies, current progresses, and underlying difficulties in using SVM for predicting the functional class of proteins. The relevant software and web-servers are described. The reported prediction performances in the application of these methods are also presented.

Derivation of stable microarray cancer-differentiating signatures using consensus scoring of multiple random sampling and gene-ranking consistency evaluation.

Microarrays have been explored for deriving molecular signatures to determine disease outcomes, mechanisms, targets, and treatment strategies. Although exhibiting good predictive performance, some derived signatures are unstable due to noises arising from measurement variability and biological differences. Improvements in measurement, annotation, and signature selection methods have been proposed. We explored a new signature selection method that incorporates consensus scoring of multiple random sampling and multistep evaluation of gene-ranking consistency for maximally avoiding erroneous elimination of predictor genes. This method was tested by using a well-studied 62-sample colon cancer data set and two other cancer data sets (86-sample lung adenocarcinoma and 60-sample hepatocellular carcinoma). For the colon cancer data set, the derived signatures of 20 sampling sets, composed of 10,000 training test sets, are fairly stable with 80% of top 50 and 69% to 93% of all predictor genes shared by all 20 signatures. These shared predictor genes include 48 cancer-related and 16 cancer-implicated genes, as well as 50% of the previously derived predictor genes. The derived signatures outperform all previously derived signatures in predicting colon cancer outcomes from an independent data set collected from the Stanford Microarray Database. Our method showed similar performance for the other two data sets, suggesting its usefulness in deriving stable signatures for biomarker and target discovery.

Computer prediction of allergen proteins from sequence-derived protein structural and physicochemical properties.

BACKGROUND: Computational methods have been developed for predicting allergen proteins from sequence segments that show identity, homology, or motif match to a known allergen. These methods achieve good prediction accuracies, but are less effective for novel proteins with no similarity to any known allergen. METHODS: This work tests the feasibility of using a statistical learning method, support vector machines, as such a method. The prediction system is trained and tested by using 1005 allergen proteins from the Allergome database and 22,469 non-allergen proteins from 7871 Pfam families. RESULTS: Testing results by an independent set of 229 allergen and 6717 non-allergen proteins from 7871 Pfam families show that 93.0% and 99.9% of these are correctly predicted, which are comparable to the best results of other methods. Of the 18 novel allergen proteins non-homologous to any other proteins in the Swissprot database, 88.9% is correctly predicted. A further screening of 168,128 proteins in the Swissprot database finds that 2.9% of the proteins are predicted as allergen proteins, which is consistent with the estimated numbers from motif-based methods. CONCLUSIONS: Our study suggests that SVM is a potentially useful method for predicting allergen proteins and it has certain capability for predicting novel allergen proteins. Our software can be accessed at .

MHC-BPS: MHC-binder prediction server for identifying peptides of flexible lengths from sequence-derived physicochemical properties.

Major histocompatibility complex (MHC)-binding peptides are essential for antigen recognition by T-cell receptors and are being explored for vaccine design. Computational methods have been developed for predicting MHC-binding peptides of fixed lengths, based on the training of relatively few non-binders. It is desirable to introduce methods applicable for peptides of flexible lengths and trained by using more diverse sets of non-binders. MHC-BPS is a web-based MHC-binder prediction server that uses support vector machines for predicting peptide binders of flexible lengths for 18 MHC class I and 12 class II alleles from sequence-derived physicochemical properties, which were trained by using 4,208 approximately 3,252 binders and 234,333 approximately 168,793 non-binders, and evaluated by an independent set of 545 approximately 476 binders and 110,564 approximately 84,430 non-binders. The binder prediction accuracies are 86 approximately 99% for 25 and 70 approximately 80% for five alleles, and the non-binder accuracies are 96 approximately 99% for 30 alleles. A screening of HIV-1 genome identifies 0.01 approximately 5% and 5 approximately 8% of the constituent peptides as binders for 24 and 6 alleles, respectively, including 75 approximately 100% of the known epitopes. This method correctly predicts 73.3% of the 15 newly published epitopes in the last 4 months of 2005. MHC-BPS is available at http://bidd.cz3.nus.edu.sg/mhc/ .

Galactosylated PVDF membrane promotes hepatocyte attachment and functional maintenance.

One of the major challenges in BLAD design is to develop functional substrates suitable for hepatocyte attachment and functional maintenance. In the present study, we designed a poly(vinylidene difluoride) (PVDF) surface coated with galactose-tethered Pluronic polymer. The galactose-derived Pluronic F68 (F68-Gal) was adsorbed on PVDF membrane through hydrophobic-hydrophobic interaction between PVDF and the polypropylene oxide segment in Pluronic. The galactose density on the modified PVDF surface increased with the concentration of the F68-Gal solution, reaching 15.4 nmol galactosyl groups per cm2 when a 1 mg/ml of F68-Gal solution was used. The adsorbed F68-Gal remained relatively stable in culture medium. Rat hepatocytes attachment efficiency on F68-Gal modified PVDF membrane was similar to that on collagen-coated surface. The attached hepatocytes on PVDF/F68-Gal membrane self-assembled into multi-cellular spheroids after 1 day of culture. These attached hepatocytes in spheroids exhibited higher cell functions such as albumin synthesis and P450 1A1 detoxification function compared to unmodified PVDF membrane and collagen-coated surface. These results suggest the potential of this galactose-immobilized PVDF membrane as a suitable substrate for hepatocyte culture.